Laboratory of Bioinformatics, Federal Research Center for Information and Computational Technologies, Novosibirsk, Russian Federation.
Specialized Educational Scientific Center, Novosibirsk State University, Novosibirsk, Russian Federation.
PLoS One. 2020 Dec 21;15(12):e0243332. doi: 10.1371/journal.pone.0243332. eCollection 2020.
Creating a complete picture of the regulation of transcription seems to be an urgent task of modern biology. Regulation of transcription is a complex process carried out by transcription factors (TFs) and auxiliary proteins. Over the past decade, ChIP-Seq has become the most common experimental technology studying genome-wide interactions between TFs and DNA. We assessed the transcriptional significance of cell line-specific features using regression analysis of ChIP-Seq datasets from the GTRD database and transcriptional start site (TSS) activities from the FANTOM5 expression atlas. For this purpose, we initially generated a large number of features that were defined as the presence or absence of TFs in different promoter regions around TSSs. Using feature selection and regression analysis, we identified sets of the most important TFs that affect expression activity of TSSs in human cell lines such as HepG2, K562 and HEK293. We demonstrated that some TFs can be classified as repressors and activators depending on their location relative to TSS.
似乎构建转录调控的全景图谱是现代生物学的一项紧迫任务。转录调控是一个由转录因子（TFs）和辅助蛋白执行的复杂过程。在过去的十年中，ChIP-Seq 已成为研究 TFs 与 DNA 之间全基因组相互作用的最常用的实验技术。我们使用来自 GTRD 数据库的 ChIP-Seq 数据集和 FANTOM5 表达图谱的转录起始位点（TSS）活性进行回归分析，评估细胞系特异性特征的转录意义。为此，我们最初生成了大量特征，这些特征被定义为 TFs 在 TSS 周围不同启动子区域的存在或不存在。通过特征选择和回归分析，我们确定了一组最重要的 TFs，这些 TFs 影响人类细胞系如 HepG2、K562 和 HEK293 中 TSS 的表达活性。我们证明，一些 TFs 可以根据它们相对于 TSS 的位置分类为抑制剂和激活剂。
